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California DMV

by io.github.pipeworx-io

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Idempotent

Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = officer change), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new FRED observations — params:{series_id:"UNRATE"}). Delivery channels: feed (always on — pull via recent_alerts or GET registry.pipeworx.io/alerts.json), and optionally email (set delivery:{email:"you@x.com"}) or sms (delivery:{sms:"+15551234567"} — phone must be verified at /account first; 10/day cap).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesSubscription type.
paramsYesType-specific filter. sec_8k: {ticker:"AAPL", items?:["5.02","1.01"]}. polymarket_edge: {topic:"fed", min_spread_bps?:500}. fred_series: {series_id:"UNRATE"}. patent_grant: {applicant:"Apple Inc."}. clinical_trial: {sponsor?:"Pfizer", condition?:"lung cancer", phase?:"PHASE3"} (sponsor or condition required).
deliveryNoOptional delivery channels in addition to the always-on persistent feed. {email:"you@x.com"} sends a templated alert per fired event. {sms:"+15551234567"} sends an SMS per event — must match the verified phone on the caller's account (verify at https://pipeworx.io/account first; 10/day cap). {webhook:"https://..."} POSTs each event JSON to your endpoint, HMAC-signed — the response includes delivery.webhook_secret (whsec_…) ONCE; verify X-Pipeworx-Signature = sha256 HMAC of "<X-Pipeworx-Timestamp>.<raw body>". Auto-disabled after 10 consecutive failing runs.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description extensively discloses behavioral traits: it returns a new subscription id, requires authentication, details type-specific parameters and delivery channels with constraints (e.g., SMS cap, webhook auto-disable, signing). This adds significant value beyond annotations, which indicate non-read-only, non-destructive, idempotent, and open-world behavior. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured, starting with the main purpose then detailing types and delivery. While comprehensive, it is slightly long; however, every sentence adds value given the complexity. It effectively front-loads key information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all necessary aspects: tool function, authentication requirements, supported types with exact parameters, all delivery channels with limitations, and the return value (subscription ID). No output schema exists, but the description adequately explains the response. The sibling tools are diverse, but the description is self-contained and complete for its complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds substantial meaning to all parameters. It provides concrete examples for each subscription type, explains the format for 'params', and details the 'delivery' object including validation rules (e.g., phone verification, webhook signing). This enriches the schema, which already has 100% coverage, with actionable guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it creates a proactive monitoring subscription and returns the subscription ID. It specifies supported types and delivery channels, making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'list_subscriptions' or 'unsubscribe', which would improve clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context for when to use the tool: to create a subscription for live-data events. It mentions the requirement of a Pipeworx OAuth account and that anonymous/BYO cannot persist subscriptions. However, it lacks explicit guidance on when not to use this tool or alternatives (e.g., for managing existing subscriptions).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.5/5.0
Disambiguation2/5

The DMV-specific tools are individually distinct, but they are buried among ~30 unrelated Pipeworx utilities with several overlapping pairs (ask_pipeworx variants, entity_profile/compare_entities/recent_changes, and the polymarket suite). An agent pointed at this server cannot reliably tell which tools belong to the California DMV domain versus the general data platform.

Naming Consistency3/5

Most tools use lowercase snake_case, and the ca_dmv_* family is consistent, but there is no coherent semantic pattern across the set: some names are noun phrases (entity_profile), some verb phrases (discover_tools, validate_claim), and many are product-specific prefixes (ask_pipeworx, polymarket_*). The formatting is consistent, but the naming conventions are mixed.

Tool Count1/5

37 tools is far too many for a California DMV server; only 6 are actually DMV-specific. The remaining ~30 tools cover general Pipeworx data lookup, prediction markets, memory, subscriptions, and AI visibility, which belong in a separate server entirely.

Completeness2/5

For the stated DMV scope, the surface is thin: it covers registrations, licenses, offices, forms, insurance codes, and EV adoption, but misses common DMV queries like registration fees, title/status lookups, and appointment or transaction data. The 30 unrelated tools do not fill these domain gaps and instead obscure them.

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